scholarly journals Evaluation of analytical performance specifications of routine clinical biochemistry tests with biological variation-based total allowable error (TEa) criteria

2018 ◽  
Author(s):  
Orhan Çakmak
Keyword(s):  
Clinical Biochemistry ◽  
Biological Variation ◽  
Analytical Performance ◽  
Total Allowable Error ◽  
Performance Specifications ◽  
Allowable Error

scholarly journals Glucose Meter Performance Criteria for Tight Glycemic Control Estimated by Simulation Modeling

2010 ◽  
Vol 56 (7) ◽  
pp. 1091-1097 ◽  
Author(s):  
Brad S Karon ◽  
James C Boyd ◽  
George G Klee
Keyword(s):  
Glycemic Control ◽  
Simulation Modeling ◽  
Total Error ◽  
Simulation Models ◽  
Tight Glycemic Control ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Total Allowable Error ◽  
Allowable Error ◽  
Glucose Meter

Abstract Background: Glucose meter analytical performance criteria required for safe and effective management of patients on tight glycemic control (TGC) are not currently defined. We used simulation modeling to relate glucose meter performance characteristics to insulin dosing errors during TGC. Methods: We used 29 920 glucose values from patients on TGC at 1 institution to represent the expected distribution of glucose values during TGC, and we used 2 different simulation models to relate glucose meter analytical performance to insulin dosing error using these 29 920 initial glucose values and assuming 10%, 15%, or 20% total allowable error (TEa) criteria. Results: One-category insulin dosing errors were common under all error conditions. Two-category insulin dosing errors occurred more frequently when either 20% or 15% TEa was assumed compared with 10% total error. Dosing errors of 3 or more categories, those most likely to result in hypoglycemia and thus patient harm, occurred infrequently under all error conditions with the exception of 20% TEa. Conclusions: Glucose meter technologies that operate within a 15% total allowable error tolerance are unlikely to produce large (≥3-category) insulin dosing errors during TGC. Increasing performance to 10% TEa should reduce the frequency of 2-category insulin dosing errors, although additional studies are necessary to determine the clinical impact of such errors during TGC. Current criteria that allow 20% total allowable error in glucose meters may not be optimal for patient management during TGC.

A fresh look at analytical performance specifications from biological variation

2013 ◽  
Vol 421 ◽  
pp. 191-192 ◽  
Author(s):  
Hedwig C.M. Stepman ◽  
Dietmar Stöckl ◽  
Patrick J. Twomey ◽  
Linda M. Thienpont
Keyword(s):  
Biological Variation ◽  
Analytical Performance ◽  
Performance Specifications

scholarly journals Implementation of biological variation-based analytical performance specifications in the laboratory: Stringent evaluation of Improvacutor blood collection tubes

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0189882
Author(s):  
Hee-Jung Chung ◽  
Yoon Kyung Song ◽  
Sung Kuk Hong ◽  
Sang-Hyun Hwang ◽  
Hee Seung Seo ◽  
...  
Keyword(s):  
Biological Variation ◽  
Analytical Performance ◽  
Blood Collection ◽  
Performance Specifications ◽  
Blood Collection Tubes

Percentiler and Flagger – low-cost, on-line monitoring of laboratory and manufacturer data and significant surplus to current external quality assessment

2018 ◽  
Vol 42 (6) ◽  
pp. 289-296 ◽  
Author(s):  
Linda M. Thienpont ◽  
Dietmar Stöckl
Keyword(s):  
Low Cost ◽  
Biological Variation ◽  
Analytical Performance ◽  
Performance Goals ◽  
Web Based ◽  
Analytical Stability ◽  
Performance Specifications ◽  
On Line ◽  
The Stability ◽  
Stability Limits

AbstractBackground:We developed two web-based applications called the “Percentiler” and “Flagger”. They use electronically sent data from the analysis of patient samples (medians in the Percentiler; % flagging in the Flagger). Through a graphical user interface, the applications allow on-line monitoring of the stability of analytical performance and flagging rate, both assessed against quality specifications. These are guided by biological variation (Percentiler) and effect of analytical instability on surrogate medical decisions (Flagger). Here, we report on the use of the applications.Methods:We constructed examples with combined observations to investigate whether the Flagger adequately translates the effect of analytical instability observed in the Percentiler, and whether the changes in the flagging rate tolerated by the proposed stability limits is realistic in combination with the analytical performance goals.Results:In general, the examples show that the most prominent flagging rates correlate well with the analytical stability and that the limits proposed for the Flagger are realistically linked to those of the Percentiler. They also show that for certain analytes the specifications for stable flagging rates can be restricted to 20% (relatively to the laboratory’s long-term flagging median) despite ambitious analytical performance goals, while for others they need to be expanded up to 70% in concordance with decreasing biological variation.Conclusions:The examples confirm that the changes in flagging rate is well related to the analytical variation, and that the proposed stability limits are fit-for-purpose. The combined observations may help individual laboratories to define realistic but ambitious performance specifications that apply for their local situation.

scholarly journals Analytical Performance Specifications for Lipoprotein(a), Apolipoprotein B-100, and Apolipoprotein A-I Using the Biological Variation Model in the EuBIVAS Population

2020 ◽  
Vol 66 (5) ◽  
pp. 727-736 ◽  
Author(s):  
Noemie Clouet-Foraison ◽  
Santica M Marcovina ◽  
Elena Guerra ◽  
Aasne K Aarsand ◽  
Abdurrahman Coşkun ◽  
...  
Keyword(s):  
Apolipoprotein B ◽  
Clinical Chemistry ◽  
Biological Variation ◽  
Analytical Performance ◽  
European Federation ◽  
Published Data ◽  
Cvd Risk ◽  
Lipoprotein A ◽  
Apolipoprotein A ◽  
Performance Specifications

Abstract Background With increased interest in lipoprotein(a) (Lp[a]) concentration as a target for risk reduction and growing clinical evidence of its impact on cardiovascular disease (CVD) risk, rigorous analytical performance specifications (APS) and accuracy targets for Lp(a) are required. We investigated the biological variation (BV) of Lp(a), and 2 other major biomarkers of CVD, apolipoprotein A-I (apoA-I) and apolipoprotein B-100 (apoB), in the European Biological Variation Study population. Method Serum samples were drawn from 91 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate on a Roche Cobas 8000 c702. Outlier, homogeneity, and trend analysis were performed, followed by CV-ANOVA to determine BV estimates and their 95% CIs. These estimates were used to calculate APS and reference change values. For Lp(a), BV estimates were determined on normalized concentration quintiles. Results Within-subject BV estimates were significantly different between sexes for Lp(a) and between women aged <50 and >50 years for apoA-I and apoB. Lp(a) APS was constant across concentration quintiles and, overall, lower than APS based on currently published data, whereas results were similar for apoA-I and apoB. Conclusion Using a fully Biological Variation Data Critical Appraisal Checklist (BIVAC)–compliant protocol, our study data confirm BV estimates of Lp(a) listed in the European Federation of Clinical Chemistry and Laboratory Medicine database and reinforce concerns expressed in recent articles regarding the suitability of older APS recommendations for Lp(a) measurements. Given the heterogeneity of Lp(a), more BIVAC-compliant studies on large numbers of individuals of different ethnic groups would be desirable.

scholarly journals European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum thyroid biomarkers based on weekly samplings from 91 healthy participants

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michela Bottani ◽  
Aasne K. Aarsand ◽  
Giuseppe Banfi ◽  
Massimo Locatelli ◽  
Abdurrahman Coşkun ◽  
...  
Keyword(s):  
Large Scale ◽  
Thyroid Stimulating Hormone ◽  
Biological Variation ◽  
Healthy Individuals ◽  
Serum Samples ◽  
Free Triiodothyronine ◽  
Performance Specifications ◽  
Study Population ◽  
Variance Homogeneity ◽  
Healthy Participants

Abstract Objectives Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT). Methods Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories; 21–69 years) on the Roche Cobas e801 at the San Raffaele Hospital (Milan, Italy). All samples from each individual were evaluated in duplicate within a single run. The BV estimates with 95% CIs were obtained by CV-ANOVA, after analysis of variance homogeneity and outliers. Results The within-subject (CV I ) BV estimates were for TSH 17.7%, FT3 5.0%, FT4 4.8%, TG 10.3, and CT 13.0%, all significantly lower than those reported in the literature. No significant differences were observed for BV estimates between men and women. Conclusions The availability of updated, in the case of CT not previously published, BV estimates for thyroid markers based on the large scale EuBIVAS study allows for refined APS and associated RCV applicable in the diagnosis and management of thyroid and related diseases.

scholarly journals Performance Criteria for Testosterone Measurements Based on Biological Variation in Adult Males: Recommendations from the Partnership for the Accurate Testing of Hormones

2012 ◽  
Vol 58 (12) ◽  
pp. 1703-1710 ◽  
Author(s):  
Yeo-Min Yun ◽  
Julianne Cook Botelho ◽  
Donald W Chandler ◽  
Alex Katayev ◽  
William L Roberts ◽  
...  
Keyword(s):  
Total Error ◽  
Full Range ◽  
Biological Variation ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Performance Goals ◽  
Adult Males ◽  
Large Variability ◽  
Wide Range ◽  
Variation Data

BACKGROUND Testosterone measurements that are accurate, reliable, and comparable across methodologies are crucial to improving public health. Current US Food and Drug Administration–cleared testosterone assays have important limitations. We sought to develop assay performance requirements on the basis of biological variation that allow physiologic changes to be distinguished from assay analytical errors. METHODS From literature review, the technical advisory subcommittee of the Partnership for the Accurate Testing of Hormones compiled a database of articles regarding analytical and biological variability of testosterone. These data, mostly from direct immunoassay-based methodologies, were used to specify analytical performance goals derived from within- and between-person variability of testosterone. RESULTS The allowable limits of desirable imprecision and bias on the basis of currently available biological variation data were 5.3% and 6.4%, respectively. The total error goal was 16.7%. From recent College of American Pathologists proficiency survey data, most currently available testosterone assays missed these analytical performance goals by wide margins. Data from the recently established CDC Hormone Standardization program showed that although the overall mean bias of selected certified assays was within 6.4%, individual sample measurements could show large variability in terms of precision, bias, and total error. CONCLUSIONS Because accurate measurement of testosterone across a wide range of concentrations [approximately 2–2000 ng/dL (0.069–69.4 nmol/L)] is important, we recommend using available data on biological variation to calculate performance criteria across the full range of expected values. Additional studies should be conducted to obtain biological variation data on testosterone from women and children, and revisions should be made to the analytical goals for these patient populations.

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